The Essential Factors of Establishing Patient-derived Tumor Model

Factors associated with engraftment success of patient-derived xenografts of breast cancer

BACKGROUND

Patient-derived xenograft (PDX) models serve as a valuable tool for the preclinical evaluation of novel therapies. They closely replicate the genetic, phenotypic, and histopathological characteristics of primary breast tumors. Despite their promise, the rate of successful PDX engraftment is various in the literature. This study aimed to identify the key factors associated with successful PDX engraftment of primary breast cancer.

METHODS

We integrated clinicopathological data with morphological attributes quantified using a trained artificial intelligence (AI) model to identify the principal factors affecting PDX engraftment.

RESULTS

Multivariate logistic regression analyses demonstrated that several factors, including a high Ki-67 labeling index (Ki-67LI) (p < 0.001), younger age at diagnosis (p = 0.032), post neoadjuvant chemotherapy (NAC) (p = 0.006), higher histologic grade (p = 0.039), larger tumor size (p = 0.029), and AI-assessed higher intratumoral necrosis (p = 0.027) and intratumoral invasive carcinoma (p = 0.040) proportions, were significant factors for successful PDX engraftment (area under the curve [AUC] 0.905). In the NAC group, a higher Ki-67LI (p < 0.001), lower Miller-Payne grade (p < 0.001), and reduced proportion of intratumoral normal breast glands as assessed by AI (p = 0.06) collectively provided excellent prediction accuracy for successful PDX engraftment (AUC 0.89).

CONCLUSIONS

We found that high Ki-67LI, younger age, post-NAC status, higher histologic grade, larger tumor size, and specific morphological attributes were significant factors for predicting successful PDX engraftment of primary breast cancer.

Advancements in Preclinical Models of Pancreatic Cancer

ABSTRACT

Pancreatic cancer remains one of the deadliest of all cancer types with a 5-year overall survival rate of just 12%. Preclinical models available for understanding the disease pathophysiology have evolved significantly in recent years. Traditionally, commercially available 2-dimensional cell lines were developed to investigate mechanisms underlying tumorigenesis, metastasis, and drug resistance. However, these cells grow as monolayer cultures that lack heterogeneity and do not effectively represent tumor biology. Developing patient-derived xenografts and genetically engineered mouse models led to increased cellular heterogeneity, molecular diversity, and tissues that histologically represent the original patient tumors. However, these models are relatively expensive and very timing consuming. More recently, the advancement of fast and inexpensive in vitro models that better mimic disease conditions in vivo are on the rise. Three-dimensional cultures like organoids and spheroids have gained popularity and are considered to recapitulate complex disease characteristics. In addition, computational genomics, transcriptomics, and metabolomic models are being developed to simulate pancreatic cancer progression and predict better treatment strategies. Herein, we review the challenges associated with pancreatic cancer research and available analytical models. We suggest that an integrated approach toward using these models may allow for developing new strategies for pancreatic cancer precision medicine.

Patient-Derived Xenografts: A Valuable Preclinical Model for Drug Development and Biomarker Discovery

Patient-derived xenografts (PDXs), established by implanting patient tumor cells into immunodeficient mice, offer a platform for faithfully replicating human tumors. They closely mimic the histopathology, genomics, and drug sensitivity of patient tumors. This chapter highlights the versatile applications of PDXs, including studying tumor biology, metastasis, and chemoresistance, as well as their use in biomarker identification, drug screening, and personalized medicine. It also addresses challenges in using PDXs in cancer research, including variations in metastatic potential, lengthy establishment timelines, stromal changes, and limitations in immunocompromised models. Despite these challenges, PDXs remain invaluable tools guiding patient treatment and advancing preclinical drug development.

Patient-Derived Xenograft Models for Translational Prostate Cancer Research and Drug Development

Patient-derived xenografts (PDXs) are a valuable preclinical research platform generated through transplantation of a patient's resected tumor into an immunodeficient or humanized mouse. PDXs serve as a high-fidelity avatar for both precision medicine and therapeutic testing against the cancer patient's disease state. While PDXs show mixed response to initial establishment, those that successfully engraft and can be sustained with serial passaging form a useful tool for basic and translational prostate cancer (PCa) research. While genetically engineered mouse (GEM) models and human cancer cell lines, and their xenografts, each play beneficial roles in discovery science and initial drug screening, PDX tumors are emerging as the gold standard approach for therapeutic proof-of-concept prior to entering clinical trial. PDXs are a powerful platform, with PCa PDXs shown to represent the original patient tumor cell population and architecture, histopathology, genomic and transcriptomic landscape, and heterogeneity. Furthermore, PDX response to anticancer drugs in mice has been closely correlated to the original patient's susceptibility to these treatments in the clinic. Several PDXs have been established and have undergone critical in-depth characterization at the cellular and molecular level across multiple PCa tumor subtypes representing both primary and metastatic patient tumors and their inherent levels of androgen responsiveness and/or treatment resistance, including androgen-sensitive, castration resistant, and neuroendocrine PCa. Multiple PDX networks and repositories have been generated for the collaborative and shared use of these vital translational cancer tools. Here we describe the creation of a PDX maintenance colony from an established well-characterized PDX, best practice for PDX maintenance in mice, and their subsequent application in preclinical drug testing. This chapter aims to serve as a go to resource for the preparation and adoption of PCa PDX models in the research laboratory and for their use as a valuable preclinical platform for translational research and therapeutic agent development.

Patient Characteristics Associated with Growth of Patient-Derived Tumor Implants in Mice (Patient-Derived Xenografts)

Background: patient-derived xenografts (PDXs) have defined the field of translational cancer research in recent years, becoming one of the most-used tools in early drug development. The process of establishing cancer models in mice has turned out to be challenging, since little research focuses on evaluating which factors impact engraftment success. We sought to determine the clinical, pathological, or molecular factors which may predict better engraftment rates in PDXs. Methods: between March 2017 and January 2021, tumor samples obtained from patients with primary or metastatic cancer were implanted into athymic nude mice. A full comprehensive evaluation of baseline factors associated with the patients and patients' tumors was performed, with the goal of potentially identifying predictive markers of engraftment. We focused on clinical (patient factors) pathological (patients' tumor samples) and molecular (patients' tumor samples) characteristics, analyzed either by immunohistochemistry (IHC) or next-generation sequencing (NGS), which were associated with the likelihood of final engraftment, as well as with tumor growth rates in xenografts. Results: a total of 585 tumor samples were collected and implanted. Twenty-one failed to engraft, due to lack of malignant cells. Of 564 tumor-positive samples, 187 (33.2%) grew at time of analysis. The study was able to find correlation and predictive value for engraftment for the following: the use of systemic antibiotics by the patient within 2 weeks of sampling (38.1% (72/189) antibiotics- group vs. 30.7% (115/375) no-antibiotics) (p = 0.048), and the administration of systemic steroids to the patients within 2 weeks of sampling (41.5% (34/48) steroids vs. 31.7% (153/329), no-steroids) (p = 0.049). Regarding patient's baseline tests, we found certain markers could help predict final engraftment success: for lactate dehydrogenase (LDH) levels, 34.1% (140/411) of tumors derived from patients with baseline blood LDH levels above the upper limit of normality (ULN) achieved growth, against 30.7% (47/153) with normal LDH (p = 0.047). Histological tumor characteristics, such as grade of differentiation, were also correlated. Grade 1: 25.4% (47/187), grade 2: 34.8% (65/187) and grade 3: 40.1% (75/187) tumors achieved successful growth (p = 0.043), suggesting the higher the grade, the higher the likelihood of success. Similarly, higher ki67 levels were also correlated with better engraftment rates: low (Ki67 < 15%): 8.9% (9/45) achieved growth vs. high (Ki67 ≥ 15%): 31% (35/113) (p: 0.002). Other markers of aggressiveness such as the presence of lymphovascular invasion in tumor sample of origin was also predictive: 42.2% (97/230) with lymphovascular vs. 26.9% (90/334) of samples with no invasion (p = 0.0001). From the molecular standpoint, mismatch-repair-deficient (MMRd) tumors showed better engraftment rates: 62.1% (18/29) achieved growth vs. 40.8% (75/184) of proficient tumors (p = 0.026). A total of 84 PDX were breast models, among which 57.9% (11/19) ER-negative models grew, vs. 15.4% (10/65) of ER-positive models (p = 0.0001), also consonant with ER-negative tumors being more aggressive. BRAFmut cancers are more likely to achieve engraftment during the development of PDX models. Lastly, tumor growth rates during first passages can help establish a cutoff point for the decision-making process during PDX development, since the higher the tumor grades, the higher the likelihood of success. Conclusions: tumors with higher grade and Ki67 protein expression, lymphovascular and/or perineural invasion, with dMMR and are negative for ER expression have a higher probability of achieving growth in the process of PDX development. The use of steroids and/or antibiotics in the patient prior to sampling can also impact the likelihood of success in PDX development. Lastly, establishing a cutoff point for tumor growth rates could guide the decision-making process during PDX development.

ABCB1 Regulates Immune Genes in Breast Cancer

Background

Resistance to standard chemotherapy is a critical problem for breast cancer patients. The ATP-binding cassette (ABC) superfamily transporters actively pump out drugs and play an important role in chemoresistance. ABCB1 (ABC subfamily B, member 1, also named as multidrug resistance protein 1, MDR1) and suppressive myeloid-derived suppressor cells (MDSCs) potentially involve in chemoresistance of breast cancer. The relationship between ABCB1 and immune genes in breast cancer has not been widely studied.

Methods

Microarray and RNA sequencing data were obtained from The Cancer Genome Atlas Breast Invasive Carcinoma in Genomic Data Commons Data Portal and Gene Expression Omnibus database. A patient-derived xenograft (PDX) model of HER2+ breast cancer was established to investigate the association between ABCB1 and immune genes in breast cancer.

Results

Expression of ABCB1 increased in doxorubicin-selected MCF-7/ADR cells. High expression of ABCB1 mRNA is correlated with lymph-node metastasis and worse overall survival in patients with breast cancer. ABCB1 is positively correlated with IL6, CSF1, CSF3, and PTGS2. In the HER2+ stage IIA breast cancer PDX model, both doxorubicin and paclitaxel suppressed growth of P2 tumors. IL6, CSF1, CSF3, and PTGS2 expression were suppressed by paclitaxel but not doxorubicin. Intrasplenic MDSCs, including CD11b+Ly6G+ and CD11b+Ly6C+ cells, were more abundant than intratumor MDSCs in PDX-carrying nude mice. Clinically, the patient developed cancer recurrence after adjuvant chemotherapy with doxorubicin-based regimen and was well controlled after paclitaxel-trastuzumab combined therapy.

Conclusion

ABCB1 was a poor predictor of HER2+ LN- breast cancer. Regulation of immune genes by ABCB1 contributed to cancer recurrence and treatment effect. The PDX model was suitable for investigation the expression of target genes and expansion of immune cells.

Patient-derived tumor models in cancer research: Evaluation of the oncostatic effects of melatonin

The development of new anticancer therapies tends to be very slow. Although their impact on potential candidates is confirmed in preclinical studies, ∼95 % of these new therapies are not approved when tested in clinical trials. One of the main reasons for this is the lack of accurate preclinical models. In this context, there are different patient-derived models, which have emerged as a powerful oncological tool: patient-derived xenografts (PDXs), patient-derived organoids (PDOs), and patient-derived cells (PDCs). Although all these models are widely applied, PDXs, which are created by engraftment of patient tumor tissues into mice, is considered more reliable. In fundamental research, the PDX model is used to evaluate drug-sensitive markers and, in clinical practice, to select a personalized therapeutic strategy. Melatonin is of particular importance in the development of innovative cancer treatments due to its oncostatic impact and lack of adverse effects. However, the literature regarding the oncostatic effect of melatonin in patient-derived tumor models is scant. This review aims to describe the important role of patient-derived models in the development of anticancer treatments, focusing, in particular, on PDX models, as well as their use in cancer research. This review also summarizes the existing literature on the anti-tumoral effect of melatonin in patient-derived models in order to propose future anti-neoplastic clinical applications.

Patient Derived Xenografts (PDX) Models as an Avatar to Assess Personalized Therapy Options in Uveal Melanoma: A Feasibility Study

Uveal melanoma is the most common primary intraocular malignancy in adults. Up to 50% of UM patients develop metastatic disease, usually in the liver. When metastatic, the prognosis is poor, and few treatment options exist. Here, we investigated the feasibility of establishing patient-derived xenografts (PDXs) from a patient's tumor in order to screen for therapies that the patient could benefit from. Samples obtained from 29 primary tumors and liver metastases of uveal melanoma were grafted into SCID mice. PDX models were successfully established for 35% of primary patient tumors and 67% of liver metastases. The tumor take rate was proportional to the risk of metastases. PDXs showed the same morphology, the same GNAQ/11, BAP1, and SF3B1 mutations, and the same chromosome 3 and 8q status as the corresponding patient samples. Six PDX models were challenged with two compounds for 4 weeks. We show that, for 31% of patients with high or intermediate risk of metastasis, the timing to obtain efficacy results on PDX models derived from their primary tumors was compatible with the selection of the therapy to treat the patient after relapse. PDXs could thus be a valid tool ("avatar") to select the best personalized therapy for one third of patients that are most at risk of relapse.

Reference genomes for BALB/c Nude and NOD/SCID mouse models

Mouse xenograft models play a vital role in tumor studies for research as well as for screening of drugs for the pharmaceutical industry. In particular, models with compromised immunity are favorable to increase the success of transplantation, such as, e.g. NOD/SCID and BALB/c Nude strains. The genomic sequence and alterations of many of these models still remain elusive and might hamper a model's further optimization or proper adapted usage. This can be in respect to treatments (e.g. NOD/SCID sensitivity to radiation), experiments or analysis of derived sequencing data of such models. Here we present the genome assemblies for the NOD/SCID and BALB/c Nude strains to overcome this short-coming for the future and improve our understanding of these models in the process. We highlight as well first insights into observed genomic differences for these models compared to the C57BL/6 reference genome. Genome assemblies for both are close to full-chromosome representations and provided with liftover annotations from the GRCm39 reference genome.

Challenges and Prospects of Patient-Derived Xenografts for Cancer Research

We discuss the importance of the in vivo models in elucidating cancer biology, focusing on the patient-derived xenograft (PDX) models, which are classic and standard functional in vivo platforms for preclinical evaluation. We provide an overview of the most representative models, including cell-derived xenografts (CDX), tumor and metastatic cell-derived xenografts, and PDX models utilizing humanized mice (HM). The orthotopic models, which could reproduce the cancer environment and its progression, similar to human tumors, are particularly common. The standard procedures and rationales of gastric adenocarcinoma (GAC) orthotopic models are addressed. Despite the significant advantages of the PDX models, such as recapitulating key features of human tumors and enabling drug testing in the in vivo context, some challenges must be acknowledged, including loss of heterogeneity, selection bias, clonal evolution, stroma replacement, tumor micro-environment (TME) changes, host cell carryover and contaminations, human-to-host cell oncogenic transformation, human and host viral infections, as well as limitations for immunologic research. To compensate for these limitations, other mouse models, such as syngeneic and humanized mouse models, are currently utilized. Overall, the PDX models represent a powerful tool in cancer research, providing critical insights into tumor biology and potential therapeutic targets, but their limitations and challenges must be carefully considered for their effective use. Lastly, we present an intronic quantitative PCR (qPCR) method to authenticate, detect, and quantify human/murine cells in cell lines and PDX samples.

Generation, evolution, interfering factors, applications, and challenges of patient-derived xenograft models in immunodeficient mice

Establishing appropriate preclinical models is essential for cancer research. Evidence suggests that cancer is a highly heterogeneous disease. This follows the growing use of cancer models in cancer research to avoid these differences between xenograft tumor models and patient tumors. In recent years, a patient-derived xenograft (PDX) tumor model has been actively generated and applied, which preserves both cell-cell interactions and the microenvironment of tumors by directly transplanting cancer tissue from tumors into immunodeficient mice. In addition to this, the advent of alternative hosts, such as zebrafish hosts, or in vitro models (organoids and microfluidics), has also facilitated the advancement of cancer research. However, they still have a long way to go before they become reliable models. The development of immunodeficient mice has enabled PDX to become more mature and radiate new vitality. As one of the most reliable and standard preclinical models, the PDX model in immunodeficient mice (PDX-IM) exerts important effects in drug screening, biomarker development, personalized medicine, co-clinical trials, and immunotherapy. Here, we focus on the development procedures and application of PDX-IM in detail, summarize the implications that the evolution of immunodeficient mice has brought to PDX-IM, and cover the key issues in developing PDX-IM in preclinical studies.

Making In Vitro Tumor Models Whole Again

As a reductionist approach, patient-derived in vitro tumor models are inherently still too simplistic for personalized drug testing as they do not capture many characteristics of the tumor microenvironment (TME), such as tumor architecture and stromal heterogeneity. This is especially problematic for assessing stromal-targeting drugs such as immunotherapies in which the density and distribution of immune and other stromal cells determine drug efficacy. On the other end, in vivo models are typically costly, low-throughput, and time-consuming to establish. Ex vivo patient-derived tumor explant (PDE) cultures involve the culture of resected tumor fragments that potentially retain the intact  TME of the original tumor. Although developed decades ago, PDE cultures have not been widely adopted likely because of their low-throughput and poor long-term viability. However, with growing recognition of the importance of patient-specific TME in mediating drug response, especially in the field of immune-oncology, there is an urgent need to resurrect these holistic cultures. In this Review, the key limitations of patient-derived tumor explant cultures are outlined and technologies that have been developed or could be employed to address these limitations are discussed. Engineered holistic tumor explant cultures may truly realize the concept of personalized medicine for cancer patients.

Experimental Murine Models for Colorectal Cancer Research

Colorectal cancer (CRC) is the third most prevalent malignancy worldwide and in both sexes. Numerous animal models for CRC have been established to study its biology, namely carcinogen-induced models (CIMs) and genetically engineered mouse models (GEMMs). CIMs are valuable for assessing colitis-related carcinogenesis and studying chemoprevention. On the other hand, CRC GEMMs have proven to be useful for evaluating the tumor microenvironment and systemic immune responses, which have contributed to the discovery of novel therapeutic approaches. Although metastatic disease can be induced by orthotopic injection of CRC cell lines, the resulting models are not representative of the full genetic diversity of the disease due to the limited number of cell lines suitable for this purpose. On the other hand, patient-derived xenografts (PDX) are the most reliable for preclinical drug development due to their ability to retain pathological and molecular characteristics. In this review, the authors discuss the various murine CRC models with a focus on their clinical relevance, benefits, and drawbacks. From all models discussed, murine CRC models will continue to be an important tool in advancing our understanding and treatment of this disease, but additional research is required to find a model that can correctly reflect the pathophysiology of CRC.

Three-Dimensional Human Bone Marrow Organoids for the Study and Application of Normal and Abnormal Hematoimmunopoiesis

Hematoimmunopoiesis takes place in the adult human bone marrow (BM), which is composed of heterogeneous niches with complex architecture that enables tight regulation of homeostatic and stress responses. There is a paucity of representative culture systems that recapitulate the heterogeneous three-dimensional (3D) human BM microenvironment and that can endogenously produce soluble factors and extracellular matrix that deliver culture fidelity for the study of both normal and abnormal hematopoiesis. Native BM lymphoid populations are also poorly represented in current in vitro and in vivo models, creating challenges for the study and treatment of BM immunopathology. BM organoid models leverage normal 3D organ structure to recreate functional niche microenvironments. Our focus herein is to review the current state of the art in the use of 3D BM organoids, focusing on their capacities to recreate critical quality attributes of the in vivo BM microenvironment for the study of human normal and abnormal hematopoiesis.

Development of a 3D Tumor Spheroid Model from the Patient's Glioblastoma Cells and Its Study by Metabolic Fluorescence Lifetime Imaging

Patient-specific in vitro tumor models are a promising platform for studying the mechanisms of oncogenesis and personalized selection of drugs. In case of glial brain tumors, development and use of such models is particularly relevant as the effectiveness of such tumor treatment remains extremely unsatisfactory. The aim of the study was to develop a model of a 3D tumor glioblastoma spheroid based on a patient's surgical material and to study its metabolic characteristics by means of fluorescence lifetime imaging microscopy of metabolic coenzymes.

Materials and Methods

The study was conducted with tumor samples from patients diagnosed with glioblastoma (Grade IV). To create spheroids, primary cultures were isolated from tumor tissue samples; the said cultures were characterized morphologically and immunocytochemically, and then planted into round-bottom ultra low-adhesion plates. The number of cells for planting was chosen empirically. The characteristics of the growth of cell cultures were compared with spheroids from glioblastomas of patients with U373 MG stable line of human glioblastoma. Visualization of autofluorescence of metabolic coenzymes of nicotinamide adenine dinucleotide (phosphate) NAD(P)H and flavin adenine dinucleotide (FAD) in spheroids was performed by means of an LSM 880 laser scanning microscope (Carl Zeiss, Germany) with a FLIM module (Becker & Hickl GmbH, Germany). The autofluorescence decay parameters were studied under normoxic and hypoxic conditions (3.5% О₂).

Results

An original protocol for 3D glioblastoma spheroids cultivation was developed. Primary glial cultures from surgical material of patients were obtained and characterized. The isolated glioblastoma cells had a spindle-shaped morphology with numerous processes and a pronounced granularity of cytoplasm. All cultures expressed glial fibrillary acidic protein (GFAP). The optimal seeding dose of 2000 cells per well was specified; its application results in formation of spheroids with a dense structure and stable growth during 7 days. The FLIM method helped to establish that spheroid cells from the patient material had a generally similar metabolism to spheroids from the stable line, however, they demonstrated more pronounced metabolic heterogeneity. Cultivation of spheroids under hypoxic conditions revealed a transition to a more glycolytic type of metabolism, which is expressed in an increase in the contribution of the free form of NAD(P)H to fluorescence decay.

Conclusion

The developed model of tumor spheroids from patients' glioblastomas in combination with the FLIM can serve as a tool to study characteristics of tumor metabolism and develop predictive tests to evaluate the effectiveness of antitumor therapy.

Donor-derived acute myeloid leukemia in solid organ transplantation

We report the transmission of acute myeloid leukemia (AML) undetected at donation from a deceased organ donor to two kidneys and one liver recipients. We reviewed the medical records, and performed molecular analyses and whole exome sequencing (WES) to ascertain AML donor origin and its molecular evolution. The liver recipient was diagnosed 11 months after transplantation and died from complications 2 months later. The two kidney recipients (R1 and R2) were diagnosed 19 and 20 months after transplantation and both received treatment for leukemia. R1 died of complications 11 months after diagnosis, while R2 went into complete remission for 44 months, before relapsing. R2 died 10 months later of complications from allogenic bone marrow transplantation. Microsatellite analysis demonstrated donor chimerism in circulating cells from both kidney recipients. Targeted molecular analyses and medical records revealed NPM1 mutation present in the donor and recipients, while FLT3 was mutated only in R1. These findings were confirmed by WES, which revealed additional founder and clonal mutations, and HLA genomic loss in R2. In conclusion, we report the first in-depth genomic analysis of AML transmission following solid organ transplantation, revealing distinct clonal evolution, and providing a potential molecular explanation for tumor escape.

The Barretos Cancer Hospital Animal Facility: Implementation and Results of a Dedicated Platform for Preclinical Oncology Models

The Barretos Cancer Hospital Animal Facility (BCHAF) is a unique facility in Brazil exclusively dedicated to working with animal models for cancer research. In this article, we briefly present our modern facility and the main experiments performed, focusing on mutant strains of mice (PTCH-knockout and ApcMin mice), xenograft models, and patient-derived xenografts (PDXs). Our results show the progress and challenges in establishing these models and the need for having an appropriate representation of our cancer population to better understand tumor biology and to identify cancer biomarkers, which could be putatively targeted, allowing for personalized therapy.

3JC48-3 (methyl 4'-methyl-5-(7-nitrobenzo[c][1,2,5]oxadiazol-4-yl)-[1,1'-biphenyl]-3-carboxylate): a novel MYC/MAX dimerization inhibitor reduces prostate cancer growth

The proto-oncogene cellular myelocytomatosis (c-Myc) is a transcription factor that is upregulated in several human cancers. Therapeutic targeting of c-Myc remains a challenge because of a disordered protein tertiary structure. The basic helical structure and zipper protein of c-Myc forms an obligate heterodimer with its partner MYC-associated factor X (MAX) to function as a transcription factor. An attractive strategy is to inhibit MYC/MAX dimerization to decrease c-Myc transcriptional function. Several methods have been described to inhibit MYC/MAX dimerization including small molecular inhibitors and proteomimetics. We studied the effect of a second-generation small molecular inhibitor 3JC48-3 on prostate cancer growth and viability. In our experimental studies, we found 3JC48-3 decreases prostate cancer cells' growth and viability in a dose-dependent fashion in vitro. We confirmed inhibition of MYC/MAX dimerization by 3JC48-3 using immunoprecipitation experiments. We have previously shown that the MYC/MAX heterodimer is a transcriptional repressor of a novel kinase protein kinase D1 (PrKD1). Treatment with 3JC48-3 upregulated PrKD1 expression and phosphorylation of known PrKD1 substrates: the threonine 120 (Thr-120) residue in beta-catenin and the serine 216 (Ser-216) in Cell Division Cycle 25 (CDC25C). The mining of gene expression in human metastatic prostate cancer samples demonstrated an inverse correlation between PrKD1 and c-Myc expression. Normal mice and mice with patient-derived prostate cancer xenografts (PDX) tolerated intraperitoneal injections of 3JC48-3 up to 100 mg/kg body weight without dose-limiting toxicity. Preliminary results in these PDX mouse models suggest that 3JC48-3 may be effective in decreasing the rate of tumor growth. In conclusion, our study demonstrates that 3JC48-3 is a potent MYC/MAX heterodimerization inhibitor that decreases prostate cancer growth and viability associated with upregulation of PrKD1 expression and kinase activity.

Patient-Derived Xenograft: A More Standard "Avatar" Model in Preclinical Studies of Gastric Cancer

Despite advances in diagnosis and treatment, gastric cancer remains the third most common cause of cancer-related death in humans. The establishment of relevant animal models of gastric cancer is critical for further research. Due to the complexity of the tumor microenvironment and the genetic heterogeneity of gastric cancer, the commonly used preclinical animal models fail to adequately represent clinically relevant models of gastric cancer. However, patient-derived models are able to replicate as much of the original inter-tumoral and intra-tumoral heterogeneity of gastric cancer as possible, reflecting the cellular interactions of the tumor microenvironment. In addition to implanting patient tissues or primary cells into immunodeficient mouse hosts for culture, the advent of alternative hosts such as humanized mouse hosts, zebrafish hosts, and in vitro culture modalities has also facilitated the advancement of gastric cancer research. This review highlights the current status, characteristics, interfering factors, and applications of patient-derived models that have emerged as more valuable preclinical tools for studying the progression and metastasis of gastric cancer.

Endometrial Cancer Patient-Derived Xenograft Models: A Systematic Review

Background: Because patient-derived xenograft (PDX) models resemble the original tumors, they can be used as platforms to find target agents for precision medicine and to study characteristics of tumor biology such as clonal evolution and microenvironment interactions. The aim of this review was to identify articles on endometrial cancer PDXs (EC-PDXs) and verify the methodology and outcomes. Methods: We used PubMed to research and identify articles on EC-PDX. The data were analyzed descriptively. Results: Post literature review, eight studies were selected for the systematic review. Eighty-five EC-PDXs were established from 173 patients with EC, with a total success rate of 49.1%. A 1–10 mm³ fragment was usually implanted. Fresh-fragment implantation had higher success rates than using overnight-stored or frozen fragments. Primary tumors were successfully established with subcutaneous implantation, but metastasis rarely occurred; orthotopic implantation via minced tumor cell injection was better for metastatic models. The success rate did not correspond to immunodeficiency grades, and PDXs using nude mice reduced costs. The tumor growth period ranged from 2 weeks to 13 months. Similar characteristics were observed between primary tumors and PDXs, including pathological findings, gene mutations, and gene expression. Conclusion: EC-PDXs are promising tools for translational research because they closely resemble the features of tumors in patients and retain molecular and histological features of the disease.

ASF1b is a novel prognostic predictor associated with cell cycle signaling pathway in gastric cancer

Gastric cancer (GC) is one of the most common malignant tumors with poor outcomes. Identification of new therapeutic targets is urgently needed. Accumulating evidence has shown that anti-silencing function 1b (ASF1b) contributes to the progression in multiple cancer types. However, detailed mechanisms of ASF1b tumorigenesis in gastric cancer remain elusive. This study showed that ASF1b was upregulated in GC tissues and remarkably correlated with TNM stage, histological grade and poor prognosis of GC. We induced down and up-regulation of ASF1b in GC cell lines and monitored the changes in their biological behavior. Furthermore, loss of ASF1b was efficient to suppress subcutaneous xenograft tumor growth in vivo. We demonstrate that ASF1b is involved in regulation of cell cycle and PI3K/AKT/mTOR signaling through experiments and database analysis. Mechanistically, ASF1b promoted the proliferation, migration and invasion of GC cells. Taken together, this study highlights the role of ASF1b, which provided new insights into the underlying mechanism of progression and metastasis in GC for the first time.

Patient-derived tumor models are attractive tools to repurpose drugs for ovarian cancer treatment: Pre-clinical updates

Despite advances in understanding of ovarian cancer biology, the progress in translation of research findings into new therapies is still slow. It is associated in part with limitations of commonly used cancer models such as cell lines and genetically engineered mouse models that lack proper representation of diversity and complexity of actual human tumors. In addition, the development of de novo anticancer drugs is a lengthy and expensive process. A promising alternative to new drug development is repurposing existing FDA-approved drugs without primary oncological purpose. These approved agents have known pharmacokinetics, pharmacodynamics, and toxicology and could be approved as anticancer drugs quicker and at lower cost. To successfully translate repurposed drugs to clinical application, an intermediate step of pre-clinical animal studies is required. To address challenges associated with reliability of tumor models for pre-clinical studies, there has been an increase in development of patient-derived xenografts (PDXs), which retain key characteristics of the original patient’s tumor, including histologic, biologic, and genetic features. The expansion and utilization of clinically and molecularly annotated PDX models derived from different ovarian cancer subtypes could substantially aid development of new therapies or rapid approval of repurposed drugs to improve treatment options for ovarian cancer patients.

Multicellular Modelling of Difficult-to-Treat Gastrointestinal Cancers: Current Possibilities and Challenges

Cancers affecting the gastrointestinal system are highly prevalent and their incidence is still increasing. Among them, gastric and pancreatic cancers have a dismal prognosis (survival of 5–20%) and are defined as difficult-to-treat cancers. This reflects the urge for novel therapeutic targets and aims for personalised therapies. As a prerequisite for identifying targets and test therapeutic interventions, the development of well-established, translational and reliable preclinical research models is instrumental. This review discusses the development, advantages and limitations of both patient-derived organoids (PDO) and patient-derived xenografts (PDX) for gastric and pancreatic ductal adenocarcinoma (PDAC). First and next generation multicellular PDO/PDX models are believed to faithfully generate a patient-specific avatar in a preclinical setting, opening novel therapeutic directions for these difficult-to-treat cancers. Excitingly, future opportunities such as PDO co-cultures with immune or stromal cells, organoid-on-a-chip models and humanised PDXs are the basis of a completely new area, offering close-to-human models. These tools can be exploited to understand cancer heterogeneity, which is indispensable to pave the way towards more tumour-specific therapies and, with that, better survival for patients.

Patient-Derived Xenografts of High-Grade Serous Ovarian Cancer Subtype as a Powerful Tool in Pre-Clinical Research

(1) Background. PDX models have become the preferred tool in research laboratories seeking to improve development and pre-clinical testing of new drugs. PDXs have been shown to capture the cellular and molecular characteristics of human tumors better than simpler cell line-based models. More recently, however, hints that PDXs may change their characteristics over time have begun to emerge, emphasizing the need for comprehensive analysis of PDX evolution. (2) Methods. We established a panel of high-grade serous ovarian carcinoma (HGSOC) PDXs and developed and validated a 300-SNP signature that can be successfully utilized to assess genetic drift across PDX passages and detect PDX contamination with lymphoproliferative tissues. In addition, we performed a detailed histological characterization and functional assessment of multiple PDX passages. (3) Results. Our data show that the PDXs remain largely stable throughout propagation, with marginal genetic drift at the time of PDX initiation and adaptation to mouse host. Importantly, our PDX lines retained the major histological characteristics of the original patients' tumors even after multiple passages in mice, demonstrating a strong concordance with the clinical responses of their corresponding patients. (4) Conclusions. Our data underline the value of defined HGSOC PDXs as a pre-clinical tumor model.

A Patient-Derived Xenograft Model of Dedifferentiated Endometrial Carcinoma: A Proof-of-Concept Study for the Identification of New Molecularly Informed Treatment Approaches

Simple Summary

Reliable animal models of human malignancies are paramount for preclinical studies of novel treatment approaches. Here, we successfully developed a patient-derived xenograft (PDX) model of dedifferentiated endometrial carcinoma (DEC)–an uncommon uterine malignancy that is generally unresponsive to standard chemo- and radiotherapy. The murine model–termed PDX-mLung–was established through the implantation of lung metastatic lesions obtained from a woman with DEC. Histologic and molecular findings revealed that PDX-mLung was highly similar to the parent human malignant lesions (both primary DEC and lung metastases). Importantly, molecular analyses revealed that PDX-mLung exhibited druggable alterations including a FGFR2 mutation and CCNE2 amplification. The former was targeted with the FGFR inhibitor lenvatinib while the latter with the cell cycle inhibitor palbociclib. The combination of the two drugs exhibited synergistic therapeutic effects against in vivo tumor growth. Collectively, these data illustrate the value of PDX models for preclinical testing of new molecularly informed therapies in difficult-to-treat gynecologic malignancies. Our results may also prompt further clinical research to examine whether the combination of lenvatinib and palbociclib has potential to improve clinical outcomes of women with DEC.

Abstract

Conventional treatment of dedifferentiated endometrial carcinoma (DEC)–an uncommon and highly aggressive uterine malignancy–is beset by high failure rates. A line of research that holds promise to overcome these limitations is tailored treatments targeted on specific molecular alterations. However, suitable preclinical platforms to allow a reliable implementation of this approach are still lacking. Here, we developed a patient-derived xenograft (PDX) model for preclinical testing of investigational drugs informed by molecular data. The model–termed PDX-mLung was established in mice implanted with lung metastatic lesions obtained from a patient with DEC. Histologic and whole-exome genetic analyses revealed a high degree of identity between PDX-mLung and the patient’s parental lesions (both primary DEC and lung metastases). Interestingly, molecular analyses revealed that PDX-mLung harbored druggable alterations including a FGFR2 mutation and CCNE2 amplification. Targeted combined treatment with the FGFR inhibitor lenvatinib and the cell cycle inhibitor palbociclib was found to exert synergistic therapeutic effects against in vivo tumor growth. Based on the results of RNA sequencing, lenvatinib and palbociclib were found to exert anti-tumor effects by interfering interferon signaling and activating hormonal pathways, respectively. Collectively, these data provide proof-of-concept evidence on the value of PDX models for preclinical testing of molecularly informed drug therapy in difficult-to-treat human malignancies. Further clinical research is needed to examine more rigorously the potential usefulness of the lenvatinib and palbociclib combination in patients with DEC.

Patient-Derived Xenograft Models in Cervical Cancer: A Systematic Review

BACKGROUND

Patient-derived xenograft (PDX) models have been a focus of attention because they closely resemble the tumor features of patients and retain the molecular and histological features of diseases. They are promising tools for translational research. In the current systematic review, we identify publications on PDX models of cervical cancer (CC-PDX) with descriptions of main methodological characteristics and outcomes to identify the most suitable method for CC-PDX.

METHODS

We searched on PubMed to identify articles reporting CC-PDX. Briefly, the main inclusion criterion for papers was description of PDX created with fragments obtained from human cervical cancer specimens, and the exclusion criterion was the creation of xenograft with established cell lines.

RESULTS

After the search process, 10 studies were found and included in the systematic review. Among 98 donor patients, 61 CC-PDX were established, and the overall success rate was 62.2%. The success rate in each article ranged from 0% to 75% and was higher when using severe immunodeficient mice such as severe combined immunodeficient (SCID), nonobese diabetic (NOD) SCID, and NOD SCID gamma (NSG) mice than nude mice. Subrenal capsule implantation led to a higher engraftment rate than orthotopic and subcutaneous implantation. Fragments with a size of 1-3 mm3 were suitable for CC-PDX. No relationship was found between the engraftment rate and characteristics of the tumor and donor patient, including histology, staging, and metastasis. The latency period varied from 10 days to 12 months. Most studies showed a strong similarity in pathological and immunohistochemical features between the original tumor and the PDX model.

CONCLUSION

Severe immunodeficient mice and subrenal capsule implantation led to a higher engraftment rate; however, orthotopic and subcutaneous implantation were alternatives. When using nude mice, subrenal implantation may be better. Fragments with a size of 1-3 mm3 were suitable for CC-PDX. Few reports have been published about CC-PDX; the results were not confirmed because of the small sample size.

A gentle introduction to understanding preclinical data for cancer pharmaco-omic modeling

A central goal of precision oncology is to administer an optimal drug treatment to each cancer patient. A common preclinical approach to tackle this problem has been to characterize the tumors of patients at the molecular and drug response levels, and employ the resulting datasets for predictive in silico modeling (mostly using machine learning). Understanding how and why the different variants of these datasets are generated is an important component of this process. This review focuses on providing such introduction aimed at scientists with little previous exposure to this research area.

Vaginal drug delivery approaches for localized management of cervical cancer

Cervical cancer or cervical intraepithelial neoplasia (CIN) remain a major public health problem among women globally. Traditional methods such as surgery are often associated with possible complications which may impact future pregnancies and childbirth especially for young female patients. Vagina with a high contact surface is a suitable route for the local and systemic delivery of drugs but its abundant mucus in continuous exchange presents a barrier for the popularization of conventional vaginal formulations including suppositories, gel, patch, creams and so on. So the development of new pharmaceutical forms based on nanotechnology became appealing owing to its several advantages such as mucosa penetration, bioadhesion, controlled drug release, and decreased adverse effects. This review provided an overview of the development of topical treatment of cervical cancer or CIN through vaginal drug delivery ranging from conventional vaginal formulations to new nanocarriers to the newly developed phototherapy and gene therapy, analyzing the problems faced by current methods used, and advising the developing trend in future. The methods of establishing preclinical animal model are also discussed.